Right Ventricular Longitudinal Strain Predicts Low-Cardiac- Output Syndrome After Surgical Aortic Valve Replacement in Patients With Preserved and Mid-range Ejection Fraction

Vasoplegia in Cardiac Surgery: A Systematic Review and Meta-analysis of Current Definitions and Their Influence on Clinical Outcomes

OBJECTIVES

To identify differences in the reported vasoplegia incidence, intensive care unit (ICU) length of stay (LOS), and 30-day mortality rates as influenced by different vasoplegia definitions used in cardiac surgery studies.

DESIGN

A systematic review was performed covering the period 1977 to 2023 using PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, and Emcare and a meta-analysis (PROSPERO: CRD42021258328) was performed.

SETTING AND PARTICIPANTS

One hundred studies defining vasoplegia in cardiac surgery patients were systematically reviewed. Sixty studies with 20 or more patients, irrespective of design, reporting vasoplegia incidence, ICU LOS, or 30-day mortality were included for meta-analysis.

INTERVENTIONS

Cardiac surgery on cardiopulmonary bypass.

MEASUREMENTS AND MAIN RESULTS

Studies were categorized depending on the used mean arterial pressure (MAP) thresholds. Random intercept logistic regression models were used for meta-analysis of incidence and mortality. Random effect meta-analysis was used for ICU LOS. One hundred studies were reviewed systematically. MAP and cardiac index thresholds varied considerably (<50-80 mmHg and 2.0-3.5 L·min-1m-2, respectively). Vasopressor dosages also differed between definitions. The reported incidence (60 studies; mean incidence, 19.9%; 95% confidence interval [CI], 16.1-24.4) varied largely between studies (2.5%-66.3%; I2 = 97%; p < 0.0001). Meta-regression models, including the MAP-threshold, did not explain this heterogeneity. Similarly, the effect of vasoplegia on ICU LOS, and 30-day mortality was very heterogeneous among studies (I2 = 99% and I2 = 73%, respectively).

CONCLUSIONS

The large variability in vasoplegia definitions is associated with significant heterogeneity regarding incidence and clinical outcomes, which cannot be explained by factors included in our models. Such variations in definitions leads to inconsistent patient diagnosis and renders published vasoplegia research incomparable.

Poor Sympathetic Compensation During Active Standing Increases the Risk of Morbidity-Mortality in the Post-Surgery of Patients with Severe Calcific Aortic Stenosis

(1) Background: Although all severe calcific aortic stenosis (SCAS) patients have decreased sympathetic compensation to active standing, it has not been studied in patients who underwent aortic valve replacement (AVR). The objective was to assess the association of the heart rate variability (HRV) response to an active orthostatic challenge before AVR with the risk of complications or death during the AVR postoperative period in patients with SCAS. (2) Methods: This observational study included 49 patients. The cardiac autonomic activity was assessed by HRV analysis during supine position and active standing (five minutes each). (3) Results: Twenty-four patients (48.9%) who presented outcomes (complication or death) had a greater left ventricular (LV) mass and a smaller magnitude of change during active standing in both the mean cardiac period and sympathetic predominance. Poor sympathetic compensation to active standing and LV mass were independently associated with the outcome odds ratio (OR) = 4.8 [(1.06, 21.8), p < 0.041] and 1.03 [(1.007, 1.062), p < 0.013], respectively. (4) Conclusions: In SCAS patients, poor sympathetic compensation in the face of orthostatic challenge and greater LV mass are associated with complications or death after AVR surgery. This approach offers an opportunity to find new criteria to reduce the surgical risk of these patients.

Right ventricular longitudinal strain in valvular heart disease: A comprehensive review

Right ventricular (RV) longitudinal strain has emerged as a crucial tool for evaluating RV systolic function in patients with heart disease. The complex anatomy of the RV presents challenges for functional assessment, traditionally conducted using conventional parameters, such as tricuspid annular plane systolic excursion and RV fractional area change. While these conventional methods are simple and practical, they have limitations in reflecting the majority of global RV systolic function. In contrast, RV longitudinal strain, measured using speckle tracking echocardiography, offers a more accurate evaluation of RV systolic function with high reproducibility. It is less dependent on angle and load and utilizes automated techniques. The utility of RV longitudinal strain in patients with valvular heart disease has been reported, showing its effectiveness in detecting early RV systolic dysfunction and providing valuable prognostic information compared to conventional methods. Treatment options for valvular heart disease include not only traditional open-heart surgery but also catheter-based interventions, which have become increasingly available in recent years. In addition to conventional risk assessment, considering treatment choices based on RV systolic function may be beneficial. This approach could provide a new method for determining the optimal treatment plan for individual patients. Despite challenges such as imaging quality and vendor-specific variability, RV longitudinal strain remains a valuable tool for early detection of RV systolic dysfunction, optimizing patient management, and improving outcomes. This review examines the clinical utility of RV longitudinal strain in patients with valvular heart disease, focusing on its prognostic value and role in patient management.

The relationship between pre-operative right ventricular longitudinal strain and low-cardiac-output syndrome after surgical aortic valve replacement

Objectives

This study was performed to investigate the relationship between right ventricular free wall longitudinal strain (RVFWSL) and low cardiac output syndrome (LCOS) after surgical aortic valve replacement (SAVR) and to further explore its association with readmission within 2 years in patients who developed LCOS after SAVR.

Methods

This single-center retrospective observational study involved consecutive patients who underwent SAVR at our hospital from May 2018 to June 2020. Preoperative echocardiography was obtained within 3 days before SAVR. The longitudinal strain of the right ventricle was analyzed using the right ventricle as the main section, and the RVFWSL and right ventricular four-chamber longitudinal strain (RV4CSL) were obtained. The primary observation was the occurrence of LCOS. The secondary prognostic indicators were mainly the readmission rates within 2 years.

Results

In total, 146 patients were finally included in this study. The RVFWSL was significantly lower in the LCOS group than in the No-LCOS group (16.63 ± 2.10) vs. (23.95 ± 6.33), respectively; P < 0.001). The multivariate regression analysis showed that the RVFWSL was associated with LCOS (odds ratio, 1.676; 95% confidence interval, 1.258-2.232; P < 0.001). The receiver operating characteristic curve showed that the cut-off value for RVFWSL to predict LCOS was less than -18.3, with an area under the curve of 0.879, sensitivity of 100%, and specificity of 80.47%. The multivariate regression analysis showed that LCOS was an independent risk factor for readmission within 2 years in patients undergoing SAVR.

Conclusion

Patients with RVFWSL (<-18.3%) may be an increased risker for LCOS after SAVR. The occurrence of LCOS after SAVR is Yong-jian Zhang a risk factor for readmission within 2 years. Right ventricular function monitoring may have some predictive value for the postoperative prognosis in patients undergoing SAVR.

Prediction of low cardiac output syndrome in patients following cardiac surgery using machine learning

Background

This study aimed to develop machine learning models to predict Low Cardiac Output Syndrome (LCOS) in patients following cardiac surgery using machine learning algorithms.

Methods

The clinical data of cardiac surgery patients in Nanjing First Hospital between June 2019 and November 2020 were retrospectively extracted from the electronic medical records. Six conventional machine learning algorithms, including logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting and light gradient boosting machine, were employed to construct the LCOS predictive models with all predictive features (full models) and selected predictive features (reduced models). The discrimination of these models was evaluated by the area under the receiver operating characteristic curve (AUC) and the calibration of the models was assessed by the calibration curve. Shapley Additive explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) were used to interpret the predictive models.

Results

Data from 1,585 patients [982 (62.0%) were male, aged 18 to 88, 212 (13.4%) with LCOS] were employed to train and validate the LCOS models. Among the full models, the RF model (AUC: 0.909, 95% CI: 0.875–0.943; Sensitivity: 0.849, 95% CI: 0.724–0.933; Specificity: 0.835, 95% CI: 0.796–0.869) and the XGB model (AUC: 0.897, 95% CI: 0.859–0.935; Sensitivity: 0.830, 95% CI: 0.702–0.919; Specificity: 0.809, 95% CI: 0.768–0.845) exhibited well predictive power for LCOS. Eleven predictive features including left ventricular ejection fraction (LVEF), first post-operative blood lactate (Lac), left ventricular diastolic diameter (LVDd), cumulative time of mean artery blood pressure (MABP) lower than 65 mmHg (MABP &lt; 65 time), hypertension history, platelets level (PLT), age, blood creatinine (Cr), total area under curve above threshold central venous pressure (CVP) 12 mmHg and 16 mmHg, and blood loss during operation were used to build the reduced models. Among the reduced models, RF model (AUC: 0.895, 95% CI: 0.857–0.933; Sensitivity: 0.830, 95% CI: 0.702–0.919; Specificity: 0.806, 95% CI: 0.765–0.843) revealed the best performance. SHAP and LIME plot showed that LVEF, Lac, LVDd and MABP &lt; 65 time significantly contributed to the prediction model.

Conclusion

In this study, we successfully developed several machine learning models to predict LCOS after surgery, which may avail to risk stratification, early detection and management of LCOS after cardiac surgery.

New developments in the understanding of right ventricular function in acute care

PURPOSE OF REVIEW

Right ventricular dysfunction has an important impact on the perioperative course of cardiac surgery patients. Recent advances in the detection and monitoring of perioperative right ventricular dysfunction will be reviewed here.

RECENT FINDINGS

The incidence of right ventricular dysfunction in cardiac surgery has been associated with unfavorable outcomes. New evidence supports the use of a pulmonary artery catheter in cardiogenic shock. The possibility to directly measure right ventricular pressure by transducing the pacing port has expanded its use to track changes in right ventricular function and to detect right ventricular outflow tract obstruction. The potential role of myocardial deformation imaging has been raised to detect patients at risk of postoperative complications.

SUMMARY

Perioperative right ventricular function monitoring is based on echocardiographic and extra-cardiac flow evaluation. In addition to imaging modalities, hemodynamic evaluation using various types of pulmonary artery catheters can be achieved to track changes rapidly and quantitatively in right ventricular function perioperatively. These monitoring techniques can be applied during and after surgery to increase the detection rate of right ventricular dysfunction. All this to improve the treatment of patients presenting early signs of right ventricular dysfunction before systemic organ dysfunction ensue.

The Predictive Value of Right Ventricular Longitudinal Strain in Pulmonary Hypertension, Heart Failure, and Valvular Diseases

Right ventricular (RV) systolic function has an important role in the prediction of adverse outcomes, including mortality, in a wide range of cardiovascular (CV) conditions. Because of complex RV geometry and load dependency of the RV functional parameters, conventional echocardiographic parameters such as RV fractional area change (FAC) and tricuspid annular plane systolic excursion (TAPSE), have limited prognostic power in a large number of patients. RV longitudinal strain overcame the majority of these limitations, as it is angle-independent, less load-dependent, highly reproducible, and measure regional myocardial deformation. It has a high predictive value in patients with pulmonary hypertension, heart failure, congenital heart disease, ischemic heart disease, pulmonary embolism, cardiomyopathies, and valvular disease. It enables detection of subclinical RV damage even when conventional parameters of RV systolic function are in the normal range. Even though cardiac magnetic resonance-derived RV longitudinal strain showed excellent predictive value, echocardiography-derived RV strain remains the method of choice for evaluation of RV mechanics primarily due to high availability. Despite a constantly growing body of evidence that support RV longitudinal strain evaluation in the majority of CV patients, its assessment has not become the part of the routine echocardiographic examination in the majority of echocardiographic laboratories. The aim of this clinical review was to summarize the current data about the predictive value of RV longitudinal strain in patients with pulmonary hypertension, heart failure and valvular heart diseases.